Cloud Based Document Understanding System
DOI:
https://doi.org/10.4108/eetiot.5390Keywords:
Cloud-based system, Document understanding, Natural language processing, Optical character recognition, OCR, Text extraction, ScalabilityAbstract
In recent years, the popularity of cloud-based systems has been on the rise, particularly in the field of document management. One of the main challenges in this area is the need for effective document understanding, which involves the extraction of meaningful information from unstructured data. To address this challenge, we propose a cloud-based document understanding system that leverages state-of-the-art machine learning techniques and natural language processing algorithms.
This system utilizes a combination of optical character recognition (OCR), text extraction, and machine learning models to extract and classify relevant information from documents. The system is designed to be scalable and flexible, allowing it to handle large volumes of data and adapt to different document types and formats. Additionally, our system employs advanced security measures to ensure the confidentiality and integrity of the processed data.
This cloud-based document understanding system has the potential to significantly improve document management processes in various industries, including healthcare, legal, and finance.
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